RICS Big Data

A guide to AI and its importance to property

VTS Gijo MathewCommercial real estate is frequently told that AI will transform the sector. While it will certainly have a huge impact, the term AI is overused and often misunderstood, writes Gijo Mathew.

AI is an umbrella term capturing everything from research on how to create a machine which mimics human thought to technology that processes data and ‘learns’ from the patterns within it.

The latter is known as ‘machine learning technology’, and it is this aspect of AI that has the potential to revolutionise commercial real estate and the core of how it operates.

Why is AI important to CRE?

Once implemented, the technology will be able to streamline previously manual processes to reduce operation costs, drive efficiency and enable CRE professionals to make data-backed decisions.

It will have an unlimited number of uses and applications with the capacity to empower us to predict when a deal will close, forecast market trends, and understand the best utilisation of an asset.

How do you get started with AI?

To make any of this possible, the data that the machine needs to learn from must exist in the first place.

Moreover, we need to have the right kind of data. It must be clean and high-quality, while providing the historical data needed to demonstrate trends and changes over time.

Companies must start putting strategies in place to collect this data now, otherwise they risk falling behind.

The commercial real estate industry is notoriously resistant towards digital transformation but we have begun to see a shift over the past few years towards the property industry investing further in data-led strategies.

As the market becomes increasingly competitive, building on this initial first step of collecting data and then having access to the machine learning technology will become imperative.

Will AI take our jobs?

AI is often feared due to concerns over the displacement of jobs and an overall loss of employment, but we dispute this. CRE is a relationship-driven industry and one of the most important aspects of machine learning is that the insights produced by the technology will have the most value if they are used to support the work of employees.

For example, it is likely that AI will support property management by automating and digitally managing tasks such as lease negotiations, tenant applications, finances, and profit goals. It can also support in quickly identifying potential tenants, which will reduce vacancy times and enable building owners to automate building functions, ensuring maximum energy efficiency and identifying irregularities in real-time.

By utilising AI, CRE professionals will be able to divert their time away from sourcing information and towards interpreting the data sourced. Their analysis will move from being a hunch to being data-backed and, while it may take the same time as the manual method, it will be much more reliable.

What role will people have when working with AI?

Incorporating AI into company strategies will not mean reducing the number of employees, particularly not immediately after its implementation.

The machines may be fast and accurate but, ultimately, are not intuitive or creative. AI cannot spot the errors that a human can. The decisions being made are highly subjective and require human input, thus AI will never be able to replace the employee. Moreover, the industry tends not to trust digital data because for so long it relied on alternative solutions. By keeping CRE professionals close to the process, trust in the data will increase.

CRE companies will also need to hire professionals to maintain the machine equipment and manage the coding behind the AI. This will require additional resources within the team.

How do you roll out AI across a business?

Traditionally business has operated in silos between the sales team and the tech developers, between front of house and back office. But that can continue no more.

To truly capitalise on the value of AI, we must bring the data and technology from the back office into the front office, joining the teams to find a common ground to drive real business.

Once this has happened, companies will find that AI has become mission critical.

At VTS we are already putting this into practice by connecting the data science experts with the big data sets from customers across the platform. This is an investment in our company’s future, but we believe that by implementing these practices now our customers will have a significant advantage further down the line.

As we have repeatedly seen in the proptech space, it’ll be the early adopters who have the competitive advantage, and there will no doubt be an upskilling piece for the wider industry.

What is the risk of not adopting AI?

Over the coming years, the gap will widen between companies that use AI and those that don’t, giving those that utilise the technology a significant competitive advantage over the laggards.

Like many aspects of real estate, we will undoubtedly follow what is happening in the consumer market where many companies, such as Amazon, Nike, BMW and PepsiCo, are all adopting AI to target customers more efficiently and more accurately.

Harnessing the power of AI may be an ambitious feat, but there is a practical journey that companies should take to reap the benefits it can provide to offer them a true competitive edge.

Gijo Mathew is chief product officer at VTS

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